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Determination of the Approach to the Construction of the Neural Network Algorithm for Detection of Emergency and Pre-Emergency Situations by Multicriterial Electro-Optical System

机译:多标准光电系统用于检测紧急情况和紧急情况的神经网络算法构造方法的确定

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Determination of the approach to the construction of the neural network algorithm for detection of emergency and pre-emergency situations by multicriterial electro-optical system was performed. The analysis for forecasting and recognition of situations in the coal mine is carried out. Two approaches on forecasting of situations - autoregression and neural networks are analyzed. The advantages of neural networks to forecasting of situations were determined. Two approaches on recognition of situations: on dynamics of change concentration of one gas and on ratios of the several gases concentration are analyzed. Classification of situations in the coal mine is formulated. Admissible concentration was define for methane - up to 2%, carbon oxide - up to 0.0017%, carbon dioxide - 1%, coal dust of 150 mg/m3. The limiting concentrations for situations in coal mine are calculated. It is proposed to use MatLab for modeling neural network. Approach to creation of neural network algorithm for forecasting situation in coal mine is proposed. Structure of the neural network for forecasting situation in the coal mine is developed.
机译:确定了通过多标准光电系统检测紧急情况和事前状况的神经网络算法的构造方法。进行了煤矿形势预测与识别分析。分析了两种预测情况的方法-自回归和神经网络。确定了神经网络在情况预测中的优势。分析了两种识别情况的方法:分析了一种气体的浓度变化的动力学以及几种气体的浓度之比。制定煤矿情况分类。甲烷的最高容许浓度-最高2%,二氧化碳-最高0.0017%,二氧化碳-1%,煤尘150 mg / m 3 。计算了煤矿情况的极限浓度。建议使用MatLab对神经网络进行建模。提出了一种用于神经网络的煤矿形势预测算法的创建方法。开发了用于预测煤矿情况的神经网络结构。

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